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Parking is one basic function of autonomous vehicles. However, parking still remains difficult to be implemented, since it requires to generate a relatively long-term series of actions to reach a certain objective under complicated constraints. One recently proposed method used deep neural networks(DNN) to learn the relationship between the actual parking trajectories and the corresponding steering...
This paper employs a computational optimal control framework to develop a mission planning tool for a team of heterogeneous unmanned vehicles conducting a nominal mine countermeasures (MCM) mission. We first describe our motivation for developing vehicle-specific sensor models for unmanned surface and underwater vehicles working collaboratively to detect mines. Next, we describe the sonar detection...
This paper deals with the model of optimal maneuver of units and its implementation in the Tactical Decision Support System (TDSS). The model is designed to be used for planning the optimal movement of units (soldiers, vehicles, unmanned robots) on the battlefield. The paper is separated into three main parts. Firstly, the model of maneuver is discussed; it is divided into five independent layers:...
In many routing planning problems of the real world the available information about the problem is imprecise, vague or uncertain. In addition, decision makers work with decisions with some subjectivity. This work formulates the Team Orienteering Problem (TOP) where the scores and travel time constraints are fuzzy. The soft computing methodology proposed to solve the problem integrates fuzzy optimization...
Navigation through an intersection is a fundamental task that will enable an autonomous car to operate in a real traffic environment. Previous studies about intersection navigation generally assume vehicle to vehicle communication ability for all of the vehicles. Since this is unattainable in the near future, we focus on the scenario that vehicles on the road cannot communicate with each other. A...
Path planning for autonomous parking control is difficult and complicated because of its non-holonomic constraints. We proposed the parking path planner KPP (Korea University Path Planner) in our prior work. The purpose of this paper is to prove the advantages of KPP through quantitative and qualitative analyses. Numerical simulations have been carried out for comparison. This paper shows that KPP...
In the context of the EC-funded project Instant Mobility, we have defined a comprehensive architecture for transport and mobility applications that aim to innovate by introducing future Internet technologies to this domain. We have defined an Internet-based “multimodal travel platform” that provides information and services able to support new types of connected transport applications. The considered...
This paper focuses on motion-planning problems for high-dimensional mobile robots with nonlinear dynamics operating in complex environments. It is motivated by a recent framework that combines sampling-based motion planning in the state space with discrete search over a workspace decomposition. Building on this line of work, the premise of this paper is that the computational efficiency can be significantly...
In this paper, a cooperative driver model for a multi-agent traffic simulation is proposed. The model combines maneuver-based trajectory planning of the vehicles with a cooperative conflict resolving. The proposed model is able to provide a safe drive in complex traffic situations at the highest possible speed. The idea of the model and its feasibility have been verified in complex scenarios such...
This paper provides an overview on possibilities to design a common mission language for mission planning of heterogeneous autonomous marine robots that have to perform challenging mission scenarios as parts of a larger group over unstructured terrain. The required concept must therefore be suited for event-driven behavior of the vehicles and allow for high flexibility online. Also, in order to be...
There is widespread interest in the deployment of fleets of marine robots with the potential to roam the oceans freely and collect data at an unprecedented scale. This calls for the development of efficient algorithms for multiple vehicle motion planning that can take directly into account the capabilities of each vehicle as well as the environmental conditions and lend themselves to seamless integration...
In this paper, we present a heuristic planning approach for guarding a valuable asset by a team of autonomous unmanned surface vehicles (USVs) operating in a continuous state-action space. The team's objective is to maximize the amount of time it takes an intruder boat to reach the asset. The team must cooperatively deal with uncertainty about which boats are actual intruders, employ active blocking...
Motion planning for a formation of nonholonomic fixed-wing UAVs in environments with obstacles is a challenge especially when the operating envelope of the platform's is considered in the planning problem. This paper presents a rapid formation motion planning algorithm to determine a formation leader trajectory between a start pose and a final pose in the presence of stationary obstacles (static no-fly-zones)...
Two optimal algorithms, MTA∗ and MT-RBA∗, are presented to find the optimal yard crane (YC) job sequence for serving a fleet of vehicles for delivery and pickup jobs with scheduled deadlines and predicted vehicle arrival times. The objective is to minimize the total tardiness of incoming vehicle jobs. This is important for minimizing vessel turnaround time. In the search for an optimal job sequence,...
Currently, there are many models available which can be used to describe a driver's behaviour for a traffic simulation. Despite the number of available formalisms it is our opinion that existing approaches neglect the interplay between the simulation topology and strategic decisions of simulated drivers. Existing models either disregard strategy updates or focus on short-term strategies only. In this...
In the modeling and simulation of driving behavior, the driving manipulation converts the decision to the specific actions and outputs to the physical model of vehicle so that the manipulation is the important content of driving research. Divided the driving manipulation modeling into resources matching and task planning. It matches the operating resources by comparing the resource matrix. Introduced...
Motion planners for autonomous vehicles often involve a two-level hierarchical structure consisting of a high-level, discrete planner and a low-level trajectory generation scheme. To ensure compatibility between these two levels of planning, we previously introduced a motion planning framework based on multiple-edge transition costs in the graph used by the discrete planner. This framework is enabled...
This work focuses on developing optimal routing and camera control strategies for multiple mobile PTZ camera platforms cooperatively tracking a stochastic target moving on the ground. The vehicles are modeled as planar Dubins vehicles traveling at a fixed speed and height. The target is tracked using an Extended Kalman Consensus Filter that estimates the target location on the ground plane and the...
Traditional routing algorithms for real world AGV systems in warehouses compute static paths, which can only be adjusted to a limited degree in the event of unplanned disturbances. In our approach, we aim for a higher reactivity in such events and plan small steps of a path incrementally. The current traffic situation and also up to date time constraints for each AGV can then be considered. We compute...
This paper addresses the problem of path planning for automated guided vehicles (AGV) system in the autonomous vehicle storage and retrieval systems (AVS/RS). To solve the problem of AGV system under dynamic uncertain environment, we propose a new method by extending the framework of interactive dynamic influence diagrams (I-DIDs) with communication capabilities, called Com-I-DIDs. Our work focuses...
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